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Engineering Design for Aircraft-Based Observations of Typhoons
Wei Zhai, Chuanhai Qian, Hao Wu, Peitao Zhao, Shuo Fu, Yuedong Wang, Zechun Li
Strategic Study of CAE ›› 2025, Vol. 27 ›› Issue (2) : 86-94.
PDF(582 KB)
PDF(582 KB)
Engineering Design for Aircraft-Based Observations of Typhoons
Typhoon is the most important disaster-causing weather system in the southeast coastal area of China during summer and autumn. Using aircraft as a mobile observation platform for direct observation of typhoons can obtain critical information about typhoons' environmental fields and their core structures, thus improving the accuracy of typhoon forecasts and warnings, as well as the effectiveness of disaster prevention and mitigation. Based on the typhoon observation practices using aircraft in China and abroad, this study proposes key considerations regarding the engineering design for aircraft-based observations of typhoons, encompassing aircraft selection, construction of support bases, airborne detection equipment, flight route planning, observation data transmission, and data application and evaluation. Furthermore, the following suggestions are proposed for establishing typhoon observation operations using aircraft in China: (1) building a professional typhoon observation command center, (2) promoting typhoon observation operations that combine manned aircraft with unmanned aerial vehicles, (3) conducting typhoon observation experiments with multi-platform coordination, (4) increasing stable support for aircraft-based typhoon observation projects, and (5) initiating an international major scientific program in the field of aircraft-based observations of typhoons.
typhoon / aircraft-based observation / aircraft model selection / airborne instruments / flight route / data transmission / data application and evaluation
| [1] |
向纯怡, 许映龙, 高拴柱, 等. 2021年西北太平洋台风活动特征和预报难点分析 [J]. 气象, 2022, 48(9): 1195‒1208.
Xiang C Y, Xu Y L, Gao S Z, et al. Analysis of the characteristics and forecast difficulties of typhoon over the western North Pacific in 2021 [J]. Meteorological Monthly, 2022, 48(9): 1195‒1208.
|
| [2] |
钱奇峰, 董林, 许映龙, 等. 2022年西北太平洋和南海台风活动特征和预报难点分析 [J]. 气象, 2023, 49(10): 1254‒1266.
Qian Q F, Dong L, Xu Y L, et al. Analysis on the characteristics and forecast difficulties of the typhoons over the northwest Pacific and the South China Sea in 2022 [J]. Meteorological Monthly, 2023, 49(10): 1254‒1266.
|
| [3] |
钱传海, 端义宏, 麻素红, 等. 我国台风业务现状及其关键技术 [J]. 气象科技进展, 2012, 2(5): 36‒43.
Qian C H, Duan Y H, Ma S H, et al. The current status and future development of China operational typhoon forecasting and its key technologies [J]. Advances in Meteorological Science and Technology, 2012, 2(5): 36‒43.
|
| [4] |
Chen G M, Zhang X P, Yang M Q, et al. Performance of tropical cyclone forecasts in the western North Pacific in 2017 [J]. Tropical Cyclone Research and Review, 2021, 10(1): 1‒15.
|
| [5] |
王皘, 许映龙, 董林, 等. 2012—2021年中央气象台台风3~5 d路径预报误差分析 [J]. 海洋预报, 2022, 39(6): 25‒33.
Wang Q, Xu Y L, Dong L, et al. Analysis of typhoon track forecast errors for 3-5 days by Central Meteorological Observatory from 2012 to 2021 [J]. Marine Forecasts, 2022, 39(6): 25‒33.
|
| [6] |
Yu H, Chen G M, Zhou C, et al. Are we reaching the limit of tropical cyclone track predictability in the western North Pacific? [J]. Bulletin of the American Meteorological Society, 2022, 103(2): 410‒428.
|
| [7] |
雷小途. 无人飞机在台风探测中的应用进展 [J]. 地球科学进展, 2015, 30(2): 276‒283.
Lei X T. Progress of unmanned aerial vehicles and their application to detection of tropical cyclone [J]. Advances in Earth Science, 2015, 30(2): 276‒283.
|
| [8] |
赵兵科, 汤杰, 雷小途, 等. 近海台风立体协同观测科学试验进展 [J]. 地球科学进展, 2022, 37(8): 771‒785.
Zhao B K, Tang J, Lei X T, et al. Progress on the experiment of a multi-platform collaborative field campaign on offshore typhoon [J]. Advances in Earth Science, 2022, 37(8): 771‒785.
|
| [9] |
Gray W M, Neumann C, Tsui T L. Assessment of the role of aircraft reconnaissance on tropical cyclone analysis and forecasting [J]. Bulletin of the American Meteorological Society, 1991, 72(12): 1867‒1883.
|
| [10] |
Martin J D, Gray W M. Tropical cyclone observation and forecasting with and without aircraft reconnaissance [J]. Weather and Forecasting, 1993, 8(4): 519‒532.
|
| [11] |
Aberson S D, Black M L, Black R A, et al. Thirty years of tropical cyclone research with the noaa p-3 aircraft [J]. Bulletin of the American Meteorological Society, 2006, 87(8): 1039‒1056.
|
| [12] |
Zhang F Q, Weng Y H, Gamache J F, et al. Performance of convection-permitting hurricane initialization and prediction during 2008—2010 with ensemble data assimilation of inner-core airborne Doppler radar observations [J]. Geophysical Research Letters, 2011, 38(15): L15810.
|
| [13] |
Qian C H, Li Y, Xu Y L, et al. Tropical cyclone monitoring and analysis techniques: A review [J]. Journal of Meteorological Research, 2024, 38(2): 351‒367.
|
| [14] |
Wu C C, Lin P H, Aberson S, et al. Dropwindsonde observations for typhoon surveillance near the Taiwan region (DOTSTAR): An overview [J]. Bulletin of the American Meteorological Society, 2005, 86: 787‒790.
|
| [15] |
Tang J, Zhang J A, Chan P, et al. A direct aircraft observation of helical rolls in the tropical cyclone boundary layer [J]. Scientific Reports, 2021, 11: 18771.
|
| [16] |
Qin X H, Duan W S, Chan P W, et al. Effects of dropsonde data in field campaigns on forecasts of tropical cyclones over the western North Pacific in 2020 and the role of CNOP sensitivity [J]. Advances in Atmospheric Sciences, 2023, 40(5): 791‒803.
|
| [17] |
李杨, 马舒庆, 王国荣, 等. 利用无人机探测台风海鸥的气象要素特征 [J]. 应用气象学报, 2009, 20(5): 579‒585.
Li Y, Ma S Q, Wang G R, et al. Characteristics of meteorological elements during typhoon kalmaegi observed by unmanned aerial vehicle [J]. Journal of Applied Meteorological Science, 2009, 20(5): 579‒585.
|
| [18] |
张诚忠, 万齐林, 丁伟钰, 等. 下投探空资料在台风莫拉克路径预报的应用试验 [J]. 气象学报, 2012, 70(1): 30‒38.
Zhang C Z, Wan Q L, Ding W Y, et al. An experiment in application of the dropsonde data to forecasting the track of Typhoon Morakot [J]. Acta Meteorologica Sinica, 2012, 70(1): 30‒38.
|
| [19] |
雷小途, 雷明, 赵兵科, 等. 火箭弹下投探测台风气象参数新技术及初步试验 [J]. 科学通报, 2017, 62(32): 3789‒3796.
Lei X T, Lei M, Zhao B K, et al. New technology and experiment of rocket dropsondes for typhoon observation [J]. Chinese Science Bulletin, 2017, 62(32): 3789‒3796.
|
| [20] |
Zhang X F, Li L X, Yang R K, et al. Comprehensive marine observing experiment based on high-altitude large unmanned aerial vehicle (South China Sea experiment 2020 of the "petrel project") [J]. Advances in Atmospheric Sciences, 2021, 38(4): 531‒537.
|
| [21] |
钱传海, 李泽椿, 张福青, 等. 国际热带气旋飞机观测综述 [J]. 气象科技进展, 2012, 2(6): 6‒16.
Qian C H, Li Z C, Zhang F Q, et al. Review on international aircraft reconnaissance of tropical cyclones [J]. Advances in Meteorological Science and Technology, 2012, 2(6): 6‒16.
|
| [22] |
Majumdar S J, Aberson S D, Bishop C H, et al. A comparison of adaptive observing guidance for Atlantic tropical cyclones [J]. Monthly Weather Review, 2006, 134(9): 2354‒2372.
|
| [23] |
Wu C C, Chen J H, Majumdar S J, et al. Intercomparison of targeted observation guidance for tropical cyclones in the northwestern Pacific [J]. Monthly Weather Review, 2009, 137(8): 2471‒2492.
|
| [24] |
Sippel J A, Wu X R, Ditchek S D, et al. Impacts of assimilating additional reconnaissance data on operational GFS tropical cyclone forecasts [J]. Weather and Forecasting, 2022, 37(9): 1615‒1639.
|
| [25] |
Zawislak J, Rogers R F, Aberson S D, et al. Accomplishments of NOAA's airborne hurricane field program and a broader future approach to forecast improvement [J]. Bulletin of the American Meteorological Society, 2022, 103(2): 311‒338.
|
| [26] |
Chou K H, Wu C C, Lin P H, et al. The impact of dropwindsonde observations on typhoon track forecasts in DOTSTAR and T-PARC [J]. Monthly Weather Review, 2011, 139(6): 1728‒1743.
|
| [27] |
吴影, 陈佩燕, 雷小途. 登陆热带气旋路径和强度预报的效益评估初步研究 [J]. 热带气象学报, 2017, 33(5): 675‒682.
Wu Y, Chen P Y, Lei X T. A preliminary study on the benefit assessment of track and intensity forecast of landfall tropical cyclones [J]. Journal of Tropical Meteorology, 2017, 33(5): 675‒682.
|
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